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You searched for subject:(Robust Optimization). Showing records 1 – 30 of 408 total matches.

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Università della Svizzera italiana

1. Mutsanas, Nikos. Approximability of precedence constrained and robust scheduling problems.

Degree: 2010, Università della Svizzera italiana

 We study the approximability of scheduling problems in different contexts. We first give a short introduction to the field of scheduling theory and present a… (more)

Subjects/Keywords: Robust optimization

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APA (6th Edition):

Mutsanas, N. (2010). Approximability of precedence constrained and robust scheduling problems. (Thesis). Università della Svizzera italiana. Retrieved from http://doc.rero.ch/record/18217

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mutsanas, Nikos. “Approximability of precedence constrained and robust scheduling problems.” 2010. Thesis, Università della Svizzera italiana. Accessed November 17, 2019. http://doc.rero.ch/record/18217.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mutsanas, Nikos. “Approximability of precedence constrained and robust scheduling problems.” 2010. Web. 17 Nov 2019.

Vancouver:

Mutsanas N. Approximability of precedence constrained and robust scheduling problems. [Internet] [Thesis]. Università della Svizzera italiana; 2010. [cited 2019 Nov 17]. Available from: http://doc.rero.ch/record/18217.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mutsanas N. Approximability of precedence constrained and robust scheduling problems. [Thesis]. Università della Svizzera italiana; 2010. Available from: http://doc.rero.ch/record/18217

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Minnesota

2. Moulton, Jeffrey. Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity.

Degree: PhD, Mathematics, 2016, University of Minnesota

 Decision makers often must consider many different possible future scenarios when they make a decision. A manager must choose inventory levels to maximize profit when… (more)

Subjects/Keywords: clustering; distributionally robust optimization; fragmentation; newsvendor; robust

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APA (6th Edition):

Moulton, J. (2016). Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/182165

Chicago Manual of Style (16th Edition):

Moulton, Jeffrey. “Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity.” 2016. Doctoral Dissertation, University of Minnesota. Accessed November 17, 2019. http://hdl.handle.net/11299/182165.

MLA Handbook (7th Edition):

Moulton, Jeffrey. “Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity.” 2016. Web. 17 Nov 2019.

Vancouver:

Moulton J. Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/11299/182165.

Council of Science Editors:

Moulton J. Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/182165


Oregon State University

3. Mokhtari, Zahra. Incorporating Uncertainty in Truckload Relay Network Design.

Degree: PhD, Industrial Engineering, 2017, Oregon State University

 In a relay network for full truckload (TL) transportation, facilities known as relay points (RPs) serve as exchange points where truck drivers can exchange trailers.… (more)

Subjects/Keywords: truckload transportation; Robust optimization

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APA (6th Edition):

Mokhtari, Z. (2017). Incorporating Uncertainty in Truckload Relay Network Design. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/60591

Chicago Manual of Style (16th Edition):

Mokhtari, Zahra. “Incorporating Uncertainty in Truckload Relay Network Design.” 2017. Doctoral Dissertation, Oregon State University. Accessed November 17, 2019. http://hdl.handle.net/1957/60591.

MLA Handbook (7th Edition):

Mokhtari, Zahra. “Incorporating Uncertainty in Truckload Relay Network Design.” 2017. Web. 17 Nov 2019.

Vancouver:

Mokhtari Z. Incorporating Uncertainty in Truckload Relay Network Design. [Internet] [Doctoral dissertation]. Oregon State University; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1957/60591.

Council of Science Editors:

Mokhtari Z. Incorporating Uncertainty in Truckload Relay Network Design. [Doctoral Dissertation]. Oregon State University; 2017. Available from: http://hdl.handle.net/1957/60591


Penn State University

4. Gauthama Sankar, Aswini. Time Allocation in Projects under Uncertainty: A Robust Optimization Approach.

Degree: MS, Industrial Engineering, 2008, Penn State University

 Traditional models of project management have laid emphasis on scheduling of operations to meet deadlines. The research presented here approaches project management as a resource… (more)

Subjects/Keywords: Robust Optimization; Project Management; Uncertainty

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APA (6th Edition):

Gauthama Sankar, A. (2008). Time Allocation in Projects under Uncertainty: A Robust Optimization Approach. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/8499

Chicago Manual of Style (16th Edition):

Gauthama Sankar, Aswini. “Time Allocation in Projects under Uncertainty: A Robust Optimization Approach.” 2008. Masters Thesis, Penn State University. Accessed November 17, 2019. https://etda.libraries.psu.edu/catalog/8499.

MLA Handbook (7th Edition):

Gauthama Sankar, Aswini. “Time Allocation in Projects under Uncertainty: A Robust Optimization Approach.” 2008. Web. 17 Nov 2019.

Vancouver:

Gauthama Sankar A. Time Allocation in Projects under Uncertainty: A Robust Optimization Approach. [Internet] [Masters thesis]. Penn State University; 2008. [cited 2019 Nov 17]. Available from: https://etda.libraries.psu.edu/catalog/8499.

Council of Science Editors:

Gauthama Sankar A. Time Allocation in Projects under Uncertainty: A Robust Optimization Approach. [Masters Thesis]. Penn State University; 2008. Available from: https://etda.libraries.psu.edu/catalog/8499


University of Waterloo

5. Lawrence, Liam Shawn Pritchard. The Optimal Steady-State Control Problem.

Degree: 2019, University of Waterloo

 Many engineering systems  – including electrical power networks, chemical processing plants, and communication networks  – have a well-defined notion of an "optimal'" steady-state operating point.… (more)

Subjects/Keywords: control theory; robust control; optimization

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APA (6th Edition):

Lawrence, L. S. P. (2019). The Optimal Steady-State Control Problem. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14510

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lawrence, Liam Shawn Pritchard. “The Optimal Steady-State Control Problem.” 2019. Thesis, University of Waterloo. Accessed November 17, 2019. http://hdl.handle.net/10012/14510.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lawrence, Liam Shawn Pritchard. “The Optimal Steady-State Control Problem.” 2019. Web. 17 Nov 2019.

Vancouver:

Lawrence LSP. The Optimal Steady-State Control Problem. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/10012/14510.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lawrence LSP. The Optimal Steady-State Control Problem. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14510

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

6. Shah, Utkarsh Dinesh. An Improved Robust Optimization Approach for Scheduling Under Uncertainty.

Degree: MS, Chemical Engineering, 2017, Texas A&M University

 In practice, the uncertainty in processing time data frequently affects the feasibility of optimal solution of the nominal production scheduling problem. Using the unit-specific event-based… (more)

Subjects/Keywords: Scheduling; Robust Optimization; Multi-stage

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APA (6th Edition):

Shah, U. D. (2017). An Improved Robust Optimization Approach for Scheduling Under Uncertainty. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/165909

Chicago Manual of Style (16th Edition):

Shah, Utkarsh Dinesh. “An Improved Robust Optimization Approach for Scheduling Under Uncertainty.” 2017. Masters Thesis, Texas A&M University. Accessed November 17, 2019. http://hdl.handle.net/1969.1/165909.

MLA Handbook (7th Edition):

Shah, Utkarsh Dinesh. “An Improved Robust Optimization Approach for Scheduling Under Uncertainty.” 2017. Web. 17 Nov 2019.

Vancouver:

Shah UD. An Improved Robust Optimization Approach for Scheduling Under Uncertainty. [Internet] [Masters thesis]. Texas A&M University; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1969.1/165909.

Council of Science Editors:

Shah UD. An Improved Robust Optimization Approach for Scheduling Under Uncertainty. [Masters Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/165909


Columbia University

7. Kang, Yang. Distributionally Robust Optimization and its Applications in Machine Learning.

Degree: 2017, Columbia University

 The goal of Distributionally Robust Optimization (DRO) is to minimize the cost of running a stochastic system, under the assumption that an adversary can replace… (more)

Subjects/Keywords: Statistics; Robust optimization; Machine learning; Mathematical optimization

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APA (6th Edition):

Kang, Y. (2017). Distributionally Robust Optimization and its Applications in Machine Learning. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8WD4C1R

Chicago Manual of Style (16th Edition):

Kang, Yang. “Distributionally Robust Optimization and its Applications in Machine Learning.” 2017. Doctoral Dissertation, Columbia University. Accessed November 17, 2019. https://doi.org/10.7916/D8WD4C1R.

MLA Handbook (7th Edition):

Kang, Yang. “Distributionally Robust Optimization and its Applications in Machine Learning.” 2017. Web. 17 Nov 2019.

Vancouver:

Kang Y. Distributionally Robust Optimization and its Applications in Machine Learning. [Internet] [Doctoral dissertation]. Columbia University; 2017. [cited 2019 Nov 17]. Available from: https://doi.org/10.7916/D8WD4C1R.

Council of Science Editors:

Kang Y. Distributionally Robust Optimization and its Applications in Machine Learning. [Doctoral Dissertation]. Columbia University; 2017. Available from: https://doi.org/10.7916/D8WD4C1R


University of Toronto

8. Kaw, Neal. Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems.

Degree: 2017, University of Toronto

Most inverse optimization models impute unspecified parameters of an objective function to make an observed solution optimal for a given optimization problem. In this thesis,… (more)

Subjects/Keywords: Inverse optimization; Nonlinear programming; Robust optimization; 0796

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APA (6th Edition):

Kaw, N. (2017). Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/79311

Chicago Manual of Style (16th Edition):

Kaw, Neal. “Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems.” 2017. Masters Thesis, University of Toronto. Accessed November 17, 2019. http://hdl.handle.net/1807/79311.

MLA Handbook (7th Edition):

Kaw, Neal. “Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems.” 2017. Web. 17 Nov 2019.

Vancouver:

Kaw N. Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems. [Internet] [Masters thesis]. University of Toronto; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1807/79311.

Council of Science Editors:

Kaw N. Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems. [Masters Thesis]. University of Toronto; 2017. Available from: http://hdl.handle.net/1807/79311


Loughborough University

9. Rossetti, Gaia. Mathematical optimization techniques for cognitive radar networks.

Degree: PhD, 2018, Loughborough University

 This thesis discusses mathematical optimization techniques for waveform design in cognitive radars. These techniques have been designed with an increasing level of sophistication, starting from… (more)

Subjects/Keywords: Waveform optimization; Convex optimization; Robust optimization; Cognitive radars

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APA (6th Edition):

Rossetti, G. (2018). Mathematical optimization techniques for cognitive radar networks. (Doctoral Dissertation). Loughborough University. Retrieved from https://dspace.lboro.ac.uk/2134/33419 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937

Chicago Manual of Style (16th Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Doctoral Dissertation, Loughborough University. Accessed November 17, 2019. https://dspace.lboro.ac.uk/2134/33419 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937.

MLA Handbook (7th Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Web. 17 Nov 2019.

Vancouver:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Internet] [Doctoral dissertation]. Loughborough University; 2018. [cited 2019 Nov 17]. Available from: https://dspace.lboro.ac.uk/2134/33419 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937.

Council of Science Editors:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Doctoral Dissertation]. Loughborough University; 2018. Available from: https://dspace.lboro.ac.uk/2134/33419 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937


Loughborough University

10. Rossetti, Gaia. Mathematical optimization techniques for cognitive radar networks.

Degree: PhD, 2018, Loughborough University

 This thesis discusses mathematical optimization techniques for waveform design in cognitive radars. These techniques have been designed with an increasing level of sophistication, starting from… (more)

Subjects/Keywords: Waveform optimization; Convex optimization; Robust optimization; Cognitive radars

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APA (6th Edition):

Rossetti, G. (2018). Mathematical optimization techniques for cognitive radar networks. (Doctoral Dissertation). Loughborough University. Retrieved from http://hdl.handle.net/2134/33419

Chicago Manual of Style (16th Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Doctoral Dissertation, Loughborough University. Accessed November 17, 2019. http://hdl.handle.net/2134/33419.

MLA Handbook (7th Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Web. 17 Nov 2019.

Vancouver:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Internet] [Doctoral dissertation]. Loughborough University; 2018. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/2134/33419.

Council of Science Editors:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Doctoral Dissertation]. Loughborough University; 2018. Available from: http://hdl.handle.net/2134/33419

11. Espinoza García, Juan Carlos. Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise.

Degree: Docteur es, Sciences de gestion, 2017, Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales

L’objectif de cette thèse est de proposer des solutions efficaces à des problèmes de décision qui ont un impact sur la vie des citoyens, et… (more)

Subjects/Keywords: Optimisation robust; Modèles de choix; Robust optimization; Location problems; Choice models

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APA (6th Edition):

Espinoza García, J. C. (2017). Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise. (Doctoral Dissertation). Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales. Retrieved from http://www.theses.fr/2017ESEC0004

Chicago Manual of Style (16th Edition):

Espinoza García, Juan Carlos. “Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise.” 2017. Doctoral Dissertation, Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales. Accessed November 17, 2019. http://www.theses.fr/2017ESEC0004.

MLA Handbook (7th Edition):

Espinoza García, Juan Carlos. “Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise.” 2017. Web. 17 Nov 2019.

Vancouver:

Espinoza García JC. Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise. [Internet] [Doctoral dissertation]. Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales; 2017. [cited 2019 Nov 17]. Available from: http://www.theses.fr/2017ESEC0004.

Council of Science Editors:

Espinoza García JC. Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise. [Doctoral Dissertation]. Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales; 2017. Available from: http://www.theses.fr/2017ESEC0004


Georgia Tech

12. Lorca Galvez, Alvaro Hugo. Robust optimization for renewable energy integration in power system operations.

Degree: PhD, Industrial and Systems Engineering, 2016, Georgia Tech

Optimization provides critical support for the operation of electric power systems. As power systems evolve, enhanced operational methodologies are required, and innovative optimization models have… (more)

Subjects/Keywords: Robust optimization; Power system operations; Renewable energy

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APA (6th Edition):

Lorca Galvez, A. H. (2016). Robust optimization for renewable energy integration in power system operations. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55653

Chicago Manual of Style (16th Edition):

Lorca Galvez, Alvaro Hugo. “Robust optimization for renewable energy integration in power system operations.” 2016. Doctoral Dissertation, Georgia Tech. Accessed November 17, 2019. http://hdl.handle.net/1853/55653.

MLA Handbook (7th Edition):

Lorca Galvez, Alvaro Hugo. “Robust optimization for renewable energy integration in power system operations.” 2016. Web. 17 Nov 2019.

Vancouver:

Lorca Galvez AH. Robust optimization for renewable energy integration in power system operations. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1853/55653.

Council of Science Editors:

Lorca Galvez AH. Robust optimization for renewable energy integration in power system operations. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55653


Hong Kong University of Science and Technology

13. Sun, Ying. Majorization-minimization algorithm and its applications in robust covariance matrix estimation.

Degree: 2016, Hong Kong University of Science and Technology

 Covariance estimation has been a fundamental and long existing problem, closely related to various fields including multi-antenna communication systems, social networks, bioinformatics, and financial engineering.… (more)

Subjects/Keywords: Analysis of covariance; Estimation theory; Robust optimization

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APA (6th Edition):

Sun, Y. (2016). Majorization-minimization algorithm and its applications in robust covariance matrix estimation. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sun, Ying. “Majorization-minimization algorithm and its applications in robust covariance matrix estimation.” 2016. Thesis, Hong Kong University of Science and Technology. Accessed November 17, 2019. https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sun, Ying. “Majorization-minimization algorithm and its applications in robust covariance matrix estimation.” 2016. Web. 17 Nov 2019.

Vancouver:

Sun Y. Majorization-minimization algorithm and its applications in robust covariance matrix estimation. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2016. [cited 2019 Nov 17]. Available from: https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sun Y. Majorization-minimization algorithm and its applications in robust covariance matrix estimation. [Thesis]. Hong Kong University of Science and Technology; 2016. Available from: https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Lehigh University

14. Dong, Yang. Robust Performance Attribution Analysis in Investment Management.

Degree: PhD, Information and Systems Engineering, 2014, Lehigh University

 This dissertation investigates robust optimization models for performance attribution analysis in investment management. Specifically, an investment manager seeks to evaluate the performance of fund managers… (more)

Subjects/Keywords: Portfolio management; Robust optimization; Uncertainty; Engineering

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APA (6th Edition):

Dong, Y. (2014). Robust Performance Attribution Analysis in Investment Management. (Doctoral Dissertation). Lehigh University. Retrieved from https://preserve.lehigh.edu/etd/1474

Chicago Manual of Style (16th Edition):

Dong, Yang. “Robust Performance Attribution Analysis in Investment Management.” 2014. Doctoral Dissertation, Lehigh University. Accessed November 17, 2019. https://preserve.lehigh.edu/etd/1474.

MLA Handbook (7th Edition):

Dong, Yang. “Robust Performance Attribution Analysis in Investment Management.” 2014. Web. 17 Nov 2019.

Vancouver:

Dong Y. Robust Performance Attribution Analysis in Investment Management. [Internet] [Doctoral dissertation]. Lehigh University; 2014. [cited 2019 Nov 17]. Available from: https://preserve.lehigh.edu/etd/1474.

Council of Science Editors:

Dong Y. Robust Performance Attribution Analysis in Investment Management. [Doctoral Dissertation]. Lehigh University; 2014. Available from: https://preserve.lehigh.edu/etd/1474


Mississippi State University

15. Baez-Rivera, Yamilka Isabel. CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP.

Degree: PhD, Electrical and Computer Engineering, 2011, Mississippi State University

 <p class=Basictextdouble-spaced>The next generation of U.S. Navy ships will see the integration of the propulsion and electrical systems as part of the all-electric ship.<span style='mso-spacerun:yes'>… (more)

Subjects/Keywords: optimization; stability; shipboard power systems; robust control

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APA (6th Edition):

Baez-Rivera, Y. I. (2011). CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;

Chicago Manual of Style (16th Edition):

Baez-Rivera, Yamilka Isabel. “CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP.” 2011. Doctoral Dissertation, Mississippi State University. Accessed November 17, 2019. http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;.

MLA Handbook (7th Edition):

Baez-Rivera, Yamilka Isabel. “CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP.” 2011. Web. 17 Nov 2019.

Vancouver:

Baez-Rivera YI. CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP. [Internet] [Doctoral dissertation]. Mississippi State University; 2011. [cited 2019 Nov 17]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;.

Council of Science Editors:

Baez-Rivera YI. CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP. [Doctoral Dissertation]. Mississippi State University; 2011. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;


Columbia University

16. Qu, Qing. Nonconvex Recovery of Low-complexity Models.

Degree: 2018, Columbia University

 Today we are living in the era of big data, there is a pressing need for efficient, scalable and robust optimization methods to analyze the… (more)

Subjects/Keywords: Electrical engineering; Nonconvex programming; Robust optimization

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APA (6th Edition):

Qu, Q. (2018). Nonconvex Recovery of Low-complexity Models. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8TJ04K8

Chicago Manual of Style (16th Edition):

Qu, Qing. “Nonconvex Recovery of Low-complexity Models.” 2018. Doctoral Dissertation, Columbia University. Accessed November 17, 2019. https://doi.org/10.7916/D8TJ04K8.

MLA Handbook (7th Edition):

Qu, Qing. “Nonconvex Recovery of Low-complexity Models.” 2018. Web. 17 Nov 2019.

Vancouver:

Qu Q. Nonconvex Recovery of Low-complexity Models. [Internet] [Doctoral dissertation]. Columbia University; 2018. [cited 2019 Nov 17]. Available from: https://doi.org/10.7916/D8TJ04K8.

Council of Science Editors:

Qu Q. Nonconvex Recovery of Low-complexity Models. [Doctoral Dissertation]. Columbia University; 2018. Available from: https://doi.org/10.7916/D8TJ04K8


University of Pennsylvania

17. Fazlyab, Mahyar. Control Theoretic Methods In Analysis And Design Of Optimization Algorithms.

Degree: 2018, University of Pennsylvania

 Recently, there has been a surge of interest in incorporating tools from dynamical systems and control theory to analyze and design iterative optimization algorithms. This… (more)

Subjects/Keywords: Iterative Algorithms; Numerical Optimization; Robust Control; Engineering

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APA (6th Edition):

Fazlyab, M. (2018). Control Theoretic Methods In Analysis And Design Of Optimization Algorithms. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/3066

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Fazlyab, Mahyar. “Control Theoretic Methods In Analysis And Design Of Optimization Algorithms.” 2018. Thesis, University of Pennsylvania. Accessed November 17, 2019. https://repository.upenn.edu/edissertations/3066.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Fazlyab, Mahyar. “Control Theoretic Methods In Analysis And Design Of Optimization Algorithms.” 2018. Web. 17 Nov 2019.

Vancouver:

Fazlyab M. Control Theoretic Methods In Analysis And Design Of Optimization Algorithms. [Internet] [Thesis]. University of Pennsylvania; 2018. [cited 2019 Nov 17]. Available from: https://repository.upenn.edu/edissertations/3066.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fazlyab M. Control Theoretic Methods In Analysis And Design Of Optimization Algorithms. [Thesis]. University of Pennsylvania; 2018. Available from: https://repository.upenn.edu/edissertations/3066

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Oregon

18. Torkamani, MohamadAli. Robust Large Margin Approaches for Machine Learning in Adversarial Settings.

Degree: 2016, University of Oregon

 Machine learning algorithms are invented to learn from data and to use data to perform predictions and analyses. Many agencies are now using machine learning… (more)

Subjects/Keywords: Adversarial machine learning; Convex optimization; Customized regularization; Dropout; Robust machine learning; Robust optimization

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APA (6th Edition):

Torkamani, M. (2016). Robust Large Margin Approaches for Machine Learning in Adversarial Settings. (Thesis). University of Oregon. Retrieved from http://hdl.handle.net/1794/20677

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Torkamani, MohamadAli. “Robust Large Margin Approaches for Machine Learning in Adversarial Settings.” 2016. Thesis, University of Oregon. Accessed November 17, 2019. http://hdl.handle.net/1794/20677.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Torkamani, MohamadAli. “Robust Large Margin Approaches for Machine Learning in Adversarial Settings.” 2016. Web. 17 Nov 2019.

Vancouver:

Torkamani M. Robust Large Margin Approaches for Machine Learning in Adversarial Settings. [Internet] [Thesis]. University of Oregon; 2016. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1794/20677.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Torkamani M. Robust Large Margin Approaches for Machine Learning in Adversarial Settings. [Thesis]. University of Oregon; 2016. Available from: http://hdl.handle.net/1794/20677

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Lund

19. Knutson, Hans-Kristian. Robust Multi-objective Optimization of Rare Earth Element Chromatography.

Degree: 2016, University of Lund

 Rare earth elements comprise the metallic elements known as lanthanides as well as scandium and yttrium. They are extensively used in modern technological industries and… (more)

Subjects/Keywords: Kemiteknik; Chromatography; Rare earth elements; Modeling; Multi-objective optimization; Robust optimization; Chromatography; Rare earth elements; Modeling; Multi-objective optimization; Robust optimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Knutson, H. (2016). Robust Multi-objective Optimization of Rare Earth Element Chromatography. (Doctoral Dissertation). University of Lund. Retrieved from http://lup.lub.lu.se/record/a0e0e46e-754d-41c3-919e-852021c47b8f ; http://portal.research.lu.se/ws/files/7726935/Thesis_Hans_Kristian_Knutson_spikfil_utan_papers.pdf

Chicago Manual of Style (16th Edition):

Knutson, Hans-Kristian. “Robust Multi-objective Optimization of Rare Earth Element Chromatography.” 2016. Doctoral Dissertation, University of Lund. Accessed November 17, 2019. http://lup.lub.lu.se/record/a0e0e46e-754d-41c3-919e-852021c47b8f ; http://portal.research.lu.se/ws/files/7726935/Thesis_Hans_Kristian_Knutson_spikfil_utan_papers.pdf.

MLA Handbook (7th Edition):

Knutson, Hans-Kristian. “Robust Multi-objective Optimization of Rare Earth Element Chromatography.” 2016. Web. 17 Nov 2019.

Vancouver:

Knutson H. Robust Multi-objective Optimization of Rare Earth Element Chromatography. [Internet] [Doctoral dissertation]. University of Lund; 2016. [cited 2019 Nov 17]. Available from: http://lup.lub.lu.se/record/a0e0e46e-754d-41c3-919e-852021c47b8f ; http://portal.research.lu.se/ws/files/7726935/Thesis_Hans_Kristian_Knutson_spikfil_utan_papers.pdf.

Council of Science Editors:

Knutson H. Robust Multi-objective Optimization of Rare Earth Element Chromatography. [Doctoral Dissertation]. University of Lund; 2016. Available from: http://lup.lub.lu.se/record/a0e0e46e-754d-41c3-919e-852021c47b8f ; http://portal.research.lu.se/ws/files/7726935/Thesis_Hans_Kristian_Knutson_spikfil_utan_papers.pdf


University of Waterloo

20. Ripsman, Danielle. Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy.

Degree: 2018, University of Waterloo

 Designing conformal and equipment-compatible radiation therapy plans is essential for ensuring high-quality treatment outcomes for cancer patients. Intensity modulated radiation therapy (IMRT) is a commonly-used… (more)

Subjects/Keywords: Radiation Therapy; Optimization; Direct Aperture Optimization; Robust Optimization; IMRT; Breast Cancer; Robust Direct Aperture Optimization; DAO; RDAO

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APA (6th Edition):

Ripsman, D. (2018). Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13958

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ripsman, Danielle. “Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy.” 2018. Thesis, University of Waterloo. Accessed November 17, 2019. http://hdl.handle.net/10012/13958.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ripsman, Danielle. “Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy.” 2018. Web. 17 Nov 2019.

Vancouver:

Ripsman D. Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/10012/13958.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ripsman D. Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13958

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Penn State University

21. Solo, Christopher James. MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY.

Degree: PhD, Industrial Engineering, 2009, Penn State University

 This research involves the development of a flexible, multi-objective optimization tool for use by supply chain managers in the design and operation of manufacturing-distribution networks… (more)

Subjects/Keywords: supply chain; uncertainty; stochastic optimization; robust optimization; chance-constrained goal programming

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APA (6th Edition):

Solo, C. J. (2009). MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9709

Chicago Manual of Style (16th Edition):

Solo, Christopher James. “MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY.” 2009. Doctoral Dissertation, Penn State University. Accessed November 17, 2019. https://etda.libraries.psu.edu/catalog/9709.

MLA Handbook (7th Edition):

Solo, Christopher James. “MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY.” 2009. Web. 17 Nov 2019.

Vancouver:

Solo CJ. MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY. [Internet] [Doctoral dissertation]. Penn State University; 2009. [cited 2019 Nov 17]. Available from: https://etda.libraries.psu.edu/catalog/9709.

Council of Science Editors:

Solo CJ. MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY. [Doctoral Dissertation]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9709


University of Southern California

22. Ye, Wei. Models and algorithms for energy efficient wireless sensor networks.

Degree: PhD, Industrial & Systems Engineering, 2009, University of Southern California

 Wireless Sensor Networks (WSNs) is an area of active research in industry and academia. WSNs can be used in a wide array of applications such… (more)

Subjects/Keywords: wireless sensor networks; robust optimization; nonlinear optimization; operations research

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APA (6th Edition):

Ye, W. (2009). Models and algorithms for energy efficient wireless sensor networks. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151

Chicago Manual of Style (16th Edition):

Ye, Wei. “Models and algorithms for energy efficient wireless sensor networks.” 2009. Doctoral Dissertation, University of Southern California. Accessed November 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151.

MLA Handbook (7th Edition):

Ye, Wei. “Models and algorithms for energy efficient wireless sensor networks.” 2009. Web. 17 Nov 2019.

Vancouver:

Ye W. Models and algorithms for energy efficient wireless sensor networks. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Nov 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151.

Council of Science Editors:

Ye W. Models and algorithms for energy efficient wireless sensor networks. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151


Columbia University

23. Lu, Brian Yin. Essays on Approximation Algorithms for Robust Linear Optimization Problems.

Degree: 2016, Columbia University

 Solving optimization problems under uncertainty has been an important topic since the appearance of mathematical optimization in the mid 19th century. George Dantzig’s 1955 paper,… (more)

Subjects/Keywords: Mathematical optimization; Uncertainty (Information theory); Robust optimization; Approximation algorithms; Operations research

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APA (6th Edition):

Lu, B. Y. (2016). Essays on Approximation Algorithms for Robust Linear Optimization Problems. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8ZG6SGM

Chicago Manual of Style (16th Edition):

Lu, Brian Yin. “Essays on Approximation Algorithms for Robust Linear Optimization Problems.” 2016. Doctoral Dissertation, Columbia University. Accessed November 17, 2019. https://doi.org/10.7916/D8ZG6SGM.

MLA Handbook (7th Edition):

Lu, Brian Yin. “Essays on Approximation Algorithms for Robust Linear Optimization Problems.” 2016. Web. 17 Nov 2019.

Vancouver:

Lu BY. Essays on Approximation Algorithms for Robust Linear Optimization Problems. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2019 Nov 17]. Available from: https://doi.org/10.7916/D8ZG6SGM.

Council of Science Editors:

Lu BY. Essays on Approximation Algorithms for Robust Linear Optimization Problems. [Doctoral Dissertation]. Columbia University; 2016. Available from: https://doi.org/10.7916/D8ZG6SGM


University of New South Wales

24. Asafuddoula, Md. Development of algorithms to solve different key challenges facing design optimization.

Degree: Engineering & Information Technology, 2014, University of New South Wales

Optimization methods play an indispensable role in today’s competitive environmentand there are plenty of practical examples where such methods have been used toidentify better performing… (more)

Subjects/Keywords: Robust design optimization; Constraint handling; Many objective optimization

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APA (6th Edition):

Asafuddoula, M. (2014). Development of algorithms to solve different key challenges facing design optimization. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Asafuddoula, Md. “Development of algorithms to solve different key challenges facing design optimization.” 2014. Doctoral Dissertation, University of New South Wales. Accessed November 17, 2019. http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true.

MLA Handbook (7th Edition):

Asafuddoula, Md. “Development of algorithms to solve different key challenges facing design optimization.” 2014. Web. 17 Nov 2019.

Vancouver:

Asafuddoula M. Development of algorithms to solve different key challenges facing design optimization. [Internet] [Doctoral dissertation]. University of New South Wales; 2014. [cited 2019 Nov 17]. Available from: http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true.

Council of Science Editors:

Asafuddoula M. Development of algorithms to solve different key challenges facing design optimization. [Doctoral Dissertation]. University of New South Wales; 2014. Available from: http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true


University of Illinois – Urbana-Champaign

25. Anderson, Jesse Cole. Robust design optimization with dynamic constraints using numerical continuation.

Degree: MS, Mechanical Engineering, 2019, University of Illinois – Urbana-Champaign

 This thesis develops a framework for performing robust design optimization of objective functions constrained by differential, algebraic, and integral constraints. A successive parameter continuation method… (more)

Subjects/Keywords: continuation; optimization; robust optimization; polynomial chaos expansion; Duffing oscillator

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APA (6th Edition):

Anderson, J. C. (2019). Robust design optimization with dynamic constraints using numerical continuation. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/104728

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Anderson, Jesse Cole. “Robust design optimization with dynamic constraints using numerical continuation.” 2019. Thesis, University of Illinois – Urbana-Champaign. Accessed November 17, 2019. http://hdl.handle.net/2142/104728.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Anderson, Jesse Cole. “Robust design optimization with dynamic constraints using numerical continuation.” 2019. Web. 17 Nov 2019.

Vancouver:

Anderson JC. Robust design optimization with dynamic constraints using numerical continuation. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2019. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/2142/104728.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Anderson JC. Robust design optimization with dynamic constraints using numerical continuation. [Thesis]. University of Illinois – Urbana-Champaign; 2019. Available from: http://hdl.handle.net/2142/104728

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Georgia Tech

26. Morris, Carl. Dynamic portfolio optimization using mean-semivariance.

Degree: PhD, Industrial and Systems Engineering, 2017, Georgia Tech

 This dissertation studies the mean-semivariance portfolio optimization problem. We describe the relationship of this kind of optimization in the context of other types of portfolio… (more)

Subjects/Keywords: Multi-period stochastic optimization; Robust optimization; Portfolio optimization; Piecewise quadratic qptimization; Parametric qptimization

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APA (6th Edition):

Morris, C. (2017). Dynamic portfolio optimization using mean-semivariance. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59245

Chicago Manual of Style (16th Edition):

Morris, Carl. “Dynamic portfolio optimization using mean-semivariance.” 2017. Doctoral Dissertation, Georgia Tech. Accessed November 17, 2019. http://hdl.handle.net/1853/59245.

MLA Handbook (7th Edition):

Morris, Carl. “Dynamic portfolio optimization using mean-semivariance.” 2017. Web. 17 Nov 2019.

Vancouver:

Morris C. Dynamic portfolio optimization using mean-semivariance. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1853/59245.

Council of Science Editors:

Morris C. Dynamic portfolio optimization using mean-semivariance. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59245


Princeton University

27. Matthews, Logan Ryan. Advancing Robust Optimization for Process Systems Engineering Applications .

Degree: PhD, 2018, Princeton University

Robust optimization is a popular method for incorporating parameter uncertainty into optimization models. Whether parameters represent the price of a feedstock or product, the operability… (more)

Subjects/Keywords: Global Optimization; Optimization Under Uncertainty; Process Synthesis; Resilient Network Design; Robust Optimization

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APA (6th Edition):

Matthews, L. R. (2018). Advancing Robust Optimization for Process Systems Engineering Applications . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j

Chicago Manual of Style (16th Edition):

Matthews, Logan Ryan. “Advancing Robust Optimization for Process Systems Engineering Applications .” 2018. Doctoral Dissertation, Princeton University. Accessed November 17, 2019. http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j.

MLA Handbook (7th Edition):

Matthews, Logan Ryan. “Advancing Robust Optimization for Process Systems Engineering Applications .” 2018. Web. 17 Nov 2019.

Vancouver:

Matthews LR. Advancing Robust Optimization for Process Systems Engineering Applications . [Internet] [Doctoral dissertation]. Princeton University; 2018. [cited 2019 Nov 17]. Available from: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j.

Council of Science Editors:

Matthews LR. Advancing Robust Optimization for Process Systems Engineering Applications . [Doctoral Dissertation]. Princeton University; 2018. Available from: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j


Penn State University

28. Bekiroglu, Korkut. From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments.

Degree: PhD, Electrical Engineering, 2015, Penn State University

 Behavioral and social scientists have demonstrated the advantages of the adaptive treatments, which usually provide better results than the fixed treatment (all patients get same… (more)

Subjects/Keywords: Adaptive Intervention; Robust Treatment Design; System Identification; Atomic Norm; min-max Structured Robust Optimization

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APA (6th Edition):

Bekiroglu, K. (2015). From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/26227

Chicago Manual of Style (16th Edition):

Bekiroglu, Korkut. “From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments.” 2015. Doctoral Dissertation, Penn State University. Accessed November 17, 2019. https://etda.libraries.psu.edu/catalog/26227.

MLA Handbook (7th Edition):

Bekiroglu, Korkut. “From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments.” 2015. Web. 17 Nov 2019.

Vancouver:

Bekiroglu K. From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. [Internet] [Doctoral dissertation]. Penn State University; 2015. [cited 2019 Nov 17]. Available from: https://etda.libraries.psu.edu/catalog/26227.

Council of Science Editors:

Bekiroglu K. From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. [Doctoral Dissertation]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/26227


Clemson University

29. Dranichak, Garrett M. Robust Solutions to Uncertain Multiobjective Programs.

Degree: PhD, Mathematical Sciences, 2018, Clemson University

 Decision making in the presence of uncertainty and multiple conflicting objec-tives is a real-life issue, especially in the fields of engineering, public policy making, business… (more)

Subjects/Keywords: highly robust efficient; objective-wise uncertainty; robust multiobjective optimization; uncertain multiobjective programs

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APA (6th Edition):

Dranichak, G. M. (2018). Robust Solutions to Uncertain Multiobjective Programs. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2154

Chicago Manual of Style (16th Edition):

Dranichak, Garrett M. “Robust Solutions to Uncertain Multiobjective Programs.” 2018. Doctoral Dissertation, Clemson University. Accessed November 17, 2019. https://tigerprints.clemson.edu/all_dissertations/2154.

MLA Handbook (7th Edition):

Dranichak, Garrett M. “Robust Solutions to Uncertain Multiobjective Programs.” 2018. Web. 17 Nov 2019.

Vancouver:

Dranichak GM. Robust Solutions to Uncertain Multiobjective Programs. [Internet] [Doctoral dissertation]. Clemson University; 2018. [cited 2019 Nov 17]. Available from: https://tigerprints.clemson.edu/all_dissertations/2154.

Council of Science Editors:

Dranichak GM. Robust Solutions to Uncertain Multiobjective Programs. [Doctoral Dissertation]. Clemson University; 2018. Available from: https://tigerprints.clemson.edu/all_dissertations/2154


University of Manchester

30. Diaz Leiva, Juan Esteban. Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems.

Degree: 2016, University of Manchester

This doctoral thesis investigates the application of simulation-based optimization (SBO) as an alternative to conventional optimization techniques when the inherent uncertainty and complex features of… (more)

Subjects/Keywords: Combinatorial optimization; Genetic algorithms; Matheuristics; Meta-heuristics; Multi-objective optimization; Production planning; Robust optimization; Simulation-based optimization; Uncertainty modelling

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APA (6th Edition):

Diaz Leiva, J. E. (2016). Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199

Chicago Manual of Style (16th Edition):

Diaz Leiva, Juan Esteban. “Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems.” 2016. Doctoral Dissertation, University of Manchester. Accessed November 17, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199.

MLA Handbook (7th Edition):

Diaz Leiva, Juan Esteban. “Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems.” 2016. Web. 17 Nov 2019.

Vancouver:

Diaz Leiva JE. Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems. [Internet] [Doctoral dissertation]. University of Manchester; 2016. [cited 2019 Nov 17]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199.

Council of Science Editors:

Diaz Leiva JE. Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems. [Doctoral Dissertation]. University of Manchester; 2016. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199

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